Plugins

Project-scoped deterministic execution trace memory and zero-token session digest plugin for DSH, compiling session histories into guarded playbooks and behavior summaries with inline session_id lineage. Registers the /tmem slash command, recalls memories only on explicit file-path or error anchors in agent/pre-step (skipping unchanged repeated steps), and intercepts tools/post-execute errors and code edits with same-origin L2 fixes, failure-loop warnings, and statistical L1 co-change partner hints (skipping routine read calls when idle). Needs Python 3 on PATH (or TMEM_PYTHON) and spawns python3 -m tmem.cli with a 5-second timeout; stores all data inside each project's .tmem/ directory (no ~/.tmem/ global store) and makes no network requests. It needs Python 3 on PATH (or TMEM_PYTHON) and runs python3 -m tmem.cli synchronously, with a 5-second timeout, on every agent step and tool result; traces are stored in .tmem/ inside each project and in ~/.tmem/ shared across projects. It makes no network requests.

Hearts of Iron IV modding bundle for DeepSeek Harness: registers 15 skills covering focus trees, events, decisions, ideas, characters, technologies, localisation, GUI and error.log triage, and mounts 20 local MCP tools (a Python stdio server) to scaffold content, statically validate mods, build a SQLite FTS5 knowledge base from the vanilla game, and preview focus trees offline. Ships a 163-document reference library; requires DSH >=0.2.0 <0.3.0 and Python 3.9+ on PATH (standard library only, no game assets).

Knowledge-planet (zsxq) knowledge base toolkit: sync posts and attachments, extract docx/PDF text and images, rebuild an index, search, and self-check — pure JS, no Python. Requires a Knowledge-planet subscription and its Cookie, pasted into config.json.

Research workflow suite that registers 10 domain skills and 15 tools, curates 450 bundled research skills into 103 capability cards with an auditable per-skill ledger, and takes over research requests automatically through a system-prompt section. Tools cover real R/Python execution (off by default, two-phase preview then confirm), data gates, figure and docx auditing, .docx generation in Chinese-journal style, live PubMed search, field-level DOI verification, and cross-session project memory.

An IDE inside DeepSeek Harness with a file tree, multi-tab editor, AI assistant with model picker and API-key setup, Git panel, PTY terminal, and Python/TypeScript LSP.

Turns one journal paper PDF into a Chinese group-meeting literature report deck (.pptx) in the Nanyang Normal University physics template, plus a matching Word speaker script. Requires Python 3 with python-pptx, python-docx, Pillow and pymupdf (pypdf fallback); install them with pip install -r requirements.txt.

Local hardware monitor for DSH: a sidebar dashboard, a composer-dock CPU/memory/GPU widget, and a hardware_monitor_status tool backed by a local Python service installed separately from the repository root with install-dsh.ps1 (Windows, Python 3.10); installing only the DSH plugin leaves the panel and tool offline.

Development-preview DSH plugin to import recordings from compatible BLE recorder cards, with optional transcription and fingerprint-linked archives. Requires recorder hardware, Host Bluetooth and Python dependencies.

Turns a repository and a running system into acceptance material - database design, design specs, a user manual with screenshots, and test / go-live / acceptance reports. Sections follow GB/T 8567-88; anything it cannot verify is left blank instead of invented. Requires Python 3 with python-docx for .docx output, and Google Chrome for automatic screenshots.

Turns a repository and a software name into Chinese software copyright registration material - the 60-page source code excerpt (50 lines per page, auto-paginated), the software manual with screenshots, and the derived application-form fields (line count, language, completion date, function summary). Requires Python 3 with python-docx, and Google Chrome for screenshots.

JupyterLab-style notebook for DSH: code and output side by side with a draggable divider, outputs that stick to the viewport while a long cell scrolls, Jupyter keyboard shortcuts (a/b/dd, m/y, Shift+Enter vs Ctrl+Enter), a scissors button to delete a cell and a chip to switch it between code and Markdown. Modified fork of @beihaizb/dsh-notebook: both register the same nb_* tools, so remove the original before installing; the Python kernel you pick needs ipykernel, jupyter_client and nbformat.

Embedded closed-loop development cockpit for DeepSeek Harness: the agent builds, flashes, debug-verifies and monitors STM32 boards from one panel, while the user watches every step live - progress ladder, streaming logs, RAM/FLASH usage and decoded serial waveforms. Requires a host Python 3.10+ on PATH (the plugin cannot install it); the ARM toolchain is auto-downloaded on first use (~400 MB, Windows x64 only), and you need an STM32 board with a debug probe.

A DeepSeek Harness bundle adapted from whatcccup/cece_legal_skills (MIT) for local DOCX, PDF, TXT and Markdown redaction with human review, PDF masking, local history and optional Agent rule edits. Requires Python 3.9+ and first-run dependency downloads. Model access is needed only for rule generation; 1.3.0 is a development prerelease and Windows acceptance is pending. The upstream is a standalone offline tool/SkillHub skill, not a DSH plugin, so it cannot be installed alongside this bundle.

Drives the installed AutoCAD over COM and exposes it to the agent as 18 mcp__autocad__ tools: connect and status, cancel the current command, list registered ProgIDs, list or create documents, save, create and list layers, draw lines, circles, rectangles, polylines, arcs and text, list entities, zoom to extents, and pass any native command through. A sidebar panel owns the Python bridge process — start, stop, restart, dependency bootstrap, live logs and crash recovery — and resolves every path at runtime, so the same bundle serves both the web app and the desktop app. Windows only, Python 3.10-3.12, AutoCAD 2022-2024 documented (2024 is the default; other versions require setting CAD_PROG_ID to the matching ProgID).

One MCP tool surface over two Windows desktop-automation backends (dsh-computer-use-win and windows-mcp). Both must be installed first: dsh-computer-use-win as a DSH plugin, windows-mcp via uv tool install windows-mcp --python 3.14, then run the bundled scripts/patch-backend.mjs once (it rewrites the local windows-mcp source; without it screenshot/read_webpage/launch_app fail) and disable the standalone wincu mount. It merges their 44 tools into 29 by dropping 10 duplicates, 4 dangerous ones (PowerShell, Registry, FileSystem, Process) and 1 tool-management entry, and blocks dangerous calls before forwarding through a reversibility-graded guard.

NURBS BRep solid modeling studio with natural-language input, live 3D viewport (measure/wireframe/fit), STEP export, and agent tools driving NVIDIA usd-brep through a managed CPython venv. Needs CPython 3.12; usd-brep wheels cover 64-bit Windows and Linux only.

Windows only. Bilibili video summarizer: downloads the audio track, transcribes it locally with faster-whisper (Python + faster-whisper, about 725 MB of models on first run), then writes the analysis markdown and renders a one-page infographic PNG.

Turns a Minecraft Java save into a Blender cover or animation: scans the .mca region files for flat open ground, exports the terrain to OBJ, and drives Blender headless with MCprep materials, the BPS character rig and three-point lighting. After each render it reviews the frame with OpenCV for facing, ground contact, exposure, lighting and composition, then re-renders with adjusted parameters when a check fails. Requires Blender 4.2 LTS or newer and Python 3.10+ with opencv-python and numpy; the first run assembles the Minecraft assets with the bundled setup command.

Local-first memory and persona plugin for DeepSeek Harness: four file-backed memory layers (pinned, memory, facts, experience), editable SOUL/MOOD persona, zero-LLM session capture, BM25 recall and a themed mood card; no standalone web panel, Python service, vector database, or API key.

Use TRAE account model quota in dsh, with multi-account management, daily check-in, rotation, usage statistics, reasoning levels and model visibility. Requires Python 3.10+; the first run downloads Python dependencies.

Local art pipeline for DSH: drives the locally installed SD WebUI and ComfyUI backends through ten image_* tools and an Art Studio sidebar panel with an embedded ComfyUI canvas, post-processes with the Python shipped with those installs (rembg cutout, Real-ESRGAN upscale, seamless tiling), and writes Godot-ready assets with res:// paths once a project root is set.

Read-only DeepSeek web archive tools for DSH: list/download/search sessions, share-list, and a digest tool that compresses the 100-session history into one high-density page with activity bars and topic clusters. Write operations are intentionally not exposed (the web client rate-limits them). Requires the separately installed deepseek-ops Python client (github.com/Panniantong/deepseek-ops, by another author) with QR-code login; set scriptDir to its path.

Create Blender product scenes in DSH with editable recipes, model imports, previews and PNG/MP4 delivery; includes workbench and agent configuration.

A chemistry workbench panel in the DSH web UI. Draw structures on a Ketcher canvas (a script downloads the build; it renders locally in the browser with no backend), then compute on the current molecule with RDKit without calling a model — formula, molecular weight, exact mass, logP, TPSA, hydrogen-bond donors and acceptors, ring counts, Fsp3, stereocentres, Lipinski and Veber rule-by-rule checks, QED, PAINS/BRENK structural alerts and the Murcko scaffold, plus SMARTS substructure matching, fingerprint similarity, format conversion, standardisation and batch clean-up. A retrosynthesis tab talks to a pluggable backend (Retro* by default) over a single JSON-in/JSON-out process, and states what is missing when the backend is not installed instead of inventing a route. The calculations run in this repository's Python package (rdkit), which is installed with pip separately.